The Environment Institute and School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia.
Department of Ecology & Evolution, Univ. Lausanne, Lausanne, Switzerland.
Glob Chang Biol. 2018 Mar;24(3):1357-1370. doi: 10.1111/gcb.13935. Epub 2017 Nov 20.
Criticism has been levelled at climate-change-induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid-cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.
有人批评气候变化引起的物种分布范围变化预测没有明确考虑复杂的种群动态。然而,由于难以使用实际数据评估预测,直接比较人口统计模型与更简单的生态位模型性能的测试仍然缺乏,因此这种动态在气候变化下的相对重要性尚不确定。我们首次比较了耦合生态位-种群模型和生态位模型在预测 20 种英国繁殖鸟类在 40 年期间分布范围变化方面的技能。使用以 2010 年为中心的数据评估了以 1970 年为中心的数据校准模型的预测结果。我们发现,与仅考虑气候变化的结构更简单的模型相比,更复杂的耦合生态位-种群模型(考虑扩散和复合种群动态)在预测物种分布范围变化方面具有更高的预测准确性。然而,只有在不使用静态历史土地利用快照(在单个时间点获取)模拟对气候变化的生态响应的情况下,这些更好的预测才会实现。相比之下,在更简单的生态位模型中同时包含静态土地利用和动态气候变量可以提高对观察到的分布范围变化的预测。尽管在预测网格单元水平的范围变化方面技能较低,但生态位模型在预测范围大小的相对变化幅度方面与更复杂的模型一样好,甚至更好。因此,生态位模型可以提供物种潜在分布范围变化幅度的合理初步估计,特别是在缺乏扩散动态、人口表现的人口统计过程以及土地覆盖变化的更详细数据的情况下。